Abstract (from Frontiers in Ecology and Evolution): Tallgrass prairie ecosystems in North America are heavily degraded and require effective restoration strategies if prairie specialist taxa are to be preserved. One common management tool used to restore grassland is the application of a seed-mix of native prairie plant species. While this technique is effective in the short-term, it is critical that species' resilience to changing climate be evaluated when designing these mixes. By utilizing species distribution models (SDMs), species' bioclimatic envelopes–and thus the geographic area suitable for them–can be quantified and predicted under various future climate regimes, and current seed-mixes may be modified to include more climate resilient species or exclude more affected species. We evaluated climate response on plant functional groups to examine the generalizability of climate response among species of particular functional groups. We selected 14 prairie species representing the functional groups of cool-season and warm-season grasses, forbs, and legumes and we modeled their responses under both a moderate and more extreme predicted future. Our functional group “composite maps” show that warm-season grasses, forbs, and legumes responded similarly to other species within their functional group, while cool-season grasses showed less inter-species concordance. The value of functional group as a rough method for evaluating climate-resilience is therefore supported, but candidate cool-season grass species will require more individualized attention. This result suggests that seed-mix designers may be able to use species with more occurrence records to generate functional group-level predictions to assess the climate response of species for which there are prohibitively few occurrence records for modeling.
Science produced by the National and Regional Climate Adaptation Science Center (CASC) network must ideally be scientifically sound, relevant to a management decision, fair and respectful of stakeholders’ divergent values, and produced through a process of iterative collaboration between scientists and managers. However, research that aims to produce usable knowledge and collaborative approaches that boost usability are not common in academia or federal research programs. As a result, neither the process of creating such research nor the impacts to stakeholders are well understood or well documented. This lack of attention to the processes and impacts of collaborative scientist-stakeholder knowledge production also limits our ability to evaluate research outcomes beyond standard academic metrics such as number of peer reviewed journal publications, conference presentations, or students trained. CASC-funded researchers have previously proposed a cohort of 45 indicators for evaluating the co-production of climate knowledge by conducting a review of the academic literature, examining metrics used by other agencies to evaluate usable science, and compiling insights from experienced researchers and managers. While this research has resulted in a rich set of data, constraints on resources, such as time and funding, have limited the team to working with a small sample of case study projects from the Southwest and Northwest CASCs. This project will address the issue of scalability in evaluation, both in terms of number of projects evaluated and number of stakeholders targeted. An evaluation approach that encompasses a center’s full portfolio of projects will better enable the intercomparison of funding choices and co-production approaches. This evaluation will focus on completed projects from the North Central and South Central CASCs. Researchers will distribute a survey to targeted stakeholders in order to learn more about their interactions with project teams and their use of specific products. Results from this project will inform decisions made by the CASC network about future projects in order to ensure good stewardship of federal funds.
Grasslands in the northern Great Plains are important ecosystems that support local economies, tribal communities, livestock grazing, diverse plant and animal communities, and large-scale migrations of big game ungulates, grassland birds, and waterfowl. Climate change and variability impact how people and animals live on and interact with grasslands, and can bring more frequent droughts, fires, or new plant species that make managing these landscapes challenging. Understanding how climate change and variability will impact grassland ecosystems and their management in the 21st century first requires a synthesis of what is known across all of these scales and a gap analysis to identify key areas of focus for future research. Researchers will address this need by conducting a series of synthesis efforts to (1) identify and describe known management questions and information needs of stakeholders related to grasslands; (2) assess the state-of-the-science on climate change and variability in the northern Great Plains region; and (3) describe ecological responses to climate variability and change across the grasslands, including tipping points, changing fire patterns, spreading invasive species, changing species distributions, habitat fragmentation, and other changes in ecological communities. This project supports resource managers by providing them with the scientific information needed to make best-practice management decisions about northern Great Plains grasslands and will foster relationships with the conservation and management organizations that will utilize this science to make decisions about public lands.
Forests in the western U.S. are increasingly impacted by climate change. Warmer and drier conditions both increase fire activity in western forests and make it more difficult for forests to recover after wildfires. If forests fail to recover, they may shift to non-forest ecosystems like grasslands or shrublands. It is important to understand where fires may result in the loss of forests because forests provide a variety of ecosystem services that human communities rely on, including carbon storage, water regulation and supply, and biodiversity. Western forests are also integral for the timber industry and valued for their recreation opportunities. Anticipating future changes to forest ecosystems, particularly at local scales relevant to land and resource managers, requires an understanding of the vulnerability of forests to fire-catalyzed change. The main goal of this work is to create a vulnerability assessment that highlights geographic areas and forest types most vulnerable to fire-catalyzed ecosystem change under current and future climate change scenarios. Researchers will assess the different parts of forest vulnerability, including exposure to varying elements of climate change (e.g. temperature and moisture balance), exposure to varying types of fires (e.g. high vs. low severity fire), and sensitivity of post-fire seedlings to climate-related mortality (e.g. through water stress). Previous research findings on this topic, funded by the Joint Fire Science Program, the National Science Foundation, and NASA, are directly relevant to land managers, but require “translation” into practical and usable tools and resources. This project will rely on and strengthen communications and collaborations between researchers and federal land managers from the U.S. Forest Service and U.S. Department of the Interior bureaus through face-to-face interactions to ensure that managers have access to the science in a form that is useful. The proposed vulnerability assessment will help managers anticipate when and where wildfires will impact ecosystems in new ways, potentially causing ecosystem shifts from forested to non-forested areas, or to fundamentally different forest types.
Drought events have cost the U.S. nearly $245 billion since 1980, with costs ranging from $2 to $44 billion in any given year. However, these socio-economic losses are not the only impacts of drought. Ecosystems, fish, wildlife, and plants also suffer, and these types of drought impacts are becoming more commonplace. Further, ecosystems that recover from drought are now doing so under different climate conditions than they have experienced in the past few centuries. As temperature and precipitation patterns change, “transformational drought”, or drought events that can permanently and irreversibly alter ecosystems – such as forests converting to grasslands – are a growing threat. This type of drought has cascading implications, including the potential to alter the ability of ecosystems to provide important services to human communities. Managers of our public lands have expressed a need for baseline science to support their decision-making processes about how to best manage the ecological impacts of drought and drought recovery in the 21st century. By synthesizing the state of the science on transformational drought, researchers will provide managers with a better understanding of the potential for and the future impacts of transformational drought across the country. Researchers will also develop a case study that allows managers to explore how targeted science that is specific to ecological transformation can improve the decision-making process. The team of scientists will work closely with a group of federal land managers, including from the Bureau of Land Management, U.S. Fish and Wildlife Service, National Park Service, and U.S. Forest Service, to ensure that the project products will support federal efforts to navigate ecological transformation on these lands. Ultimately, this project will provide solutions-oriented science to help resource managers prepare for transformational drought.
Prairies were once widespread across North America, but are now one of the most endangered and least protected ecosystems in the world. Agriculture and residential development have reduced once extensive prairies into a patchwork of remnant prairies and “surrogate” grasslands (e.g., hayfields, planted pastures). Grassland ecosystems and many grassland-dependent birds are also particularly vulnerable to rapid shifts in climate and associated changes in drought and extreme weather. The Central Flyway is a vast bird migration route that comprises more than half of the continental U.S., and extends from Central America to Canada, and harbors the greatest diversity of grassland birds in North America. Throughout this region, numerous agencies and organizations are entrusted with the management of grassland ecosystems and the species that depend on them in landscapes extensively altered by human activities. Today, they face the additional challenge of managing these ecosystems in the face of a rapidly changing climate. The goal of this project is to synthesize the vulnerability of grassland ecosystems to climate change across the Central Flyway, with an emphasis on grassland-dependent migratory birds. Researchers will synthesize the state of the science, including providing a robust assessment of how climate variables directly and indirectly (via land use change) affect grassland habitats and migratory bird populations. Researchers will also review current and future adaptation strategies for the conservation of grassland ecosystems and grassland-dependent birds. This effort will result in a synthesis of key management strategies and future research needs related to the conservation of migratory grassland bird populations in the Central Flyway in the face of climate change.
The North Central Climate Adaptation Science Center (NC CASC) partnered with the Wildlife Conservation Society (WCS) and Conservation Science Partners, Inc. (CSP) to systematically identify information gaps that, if addressed, would support management decisions for key species, habitats, or other issues within the North Central region (Montana, Wyoming, Colorado, North Dakota, South Dakota, Nebraska, Kansas). In particular, we were interested in the intersection between 1) high-priority species or habitats that are 2) the subject of a planned decision, and for which 3) climate information would aid decision-making for state and federal agencies. In Spring of 2018, we interviewed state fish and wildlife managers to learn about high-priority species, habitats, and issues within the North Central region. As described in this report, the interviews generated a wealth of information about state agency priorities, and topics for which state managers think more climate change information would be useful.
Abstract (from ScienceDirect): Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R2 = 0.75) and gross primary productivity (R2 = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.